Computational translation of genomic responses from experimental model systems to humans

The high failure rate of therapeutics showing promise in mouse models to translate to patients is a pressing challenge in biomedical science. Though retrospective studies have examined the fidelity of mouse models to their respective human conditions, approaches for prospective translation of insigh...

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Veröffentlicht in:	PLoS computational biology 2019-01, Vol.15 (1), p.e1006286-e1006286
Hauptverfasser:	Brubaker, Douglas K, Proctor, Elizabeth A, Haigis, Kevin M, Lauffenburger, Douglas A
Format:	Artikel
Sprache:	eng
Schlagworte:	Acids Animal experimentation Animal models Animals Artificial intelligence Artificial neural networks Bioengineering Biology Biology and Life Sciences Biomedical materials Cancer Computation Computer and Information Sciences Computer applications Consortia Datasets Design of experiments Disease Models, Animal Engineering Experimental design Failure rates Gene expression Gene Expression Profiling - methods Genes Genetic research Genomes Genomics Genomics - methods Genotype & phenotype House mouse Humans Inference Inflammation - genetics Inflammation - metabolism Inflammatory diseases Machine learning Medical research Medicine and Health Sciences Mice Neural networks Neural Networks, Computer Ontology Phenotypes Physical Sciences Research and Analysis Methods Rodents Semi-supervised learning Sepsis Streptococcus infections Supervised Machine Learning Therapeutics Transcriptome - genetics Translation Translation (Genetics) Translational Medical Research - methods
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